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Development of Cognitive Capabilities for Smart Home Using a Self-Organizing Fuzzy Neural Network

Ray, Anjan, Leng, G, McGinnity, TM, Coleman, SA and Maguire, LP (2012) Development of Cognitive Capabilities for Smart Home Using a Self-Organizing Fuzzy Neural Network. In: 10th IFAC Symposium on Robot Control, Dubrovnik, Croatia. IFAC. 8 pp. [Conference contribution]

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DOI: 10.3182/20120905-3-HR-2030.00182


A smart home requires cognitive assistance to analyze and understand the behavior in this sensory rich environment. In this paper we explore the potential of a self-organizing fuzzy neural network (SOFNN) as a core component of a cognitive system for a smart home environment. We develop a cognitive reasoning module that has the ability to adapt its neuronal structure through adding and pruning of neurons according to the incoming data. The SOFNN rules explore the relations of the inputs and the desired reasoning outputs. The network is trained with realistic synthesized data to show its adaptation capability and is tested with unseen data to validate its cognitive capabilities. We outline the theoretical development and describe the results achieved. This initial implementation of the cognitive module demonstrates the potential of the architecture and will serve as a very important test-bed for future work.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:23428
Deposited By: Dr Sonya Coleman
Deposited On:28 Sep 2012 11:37
Last Modified:28 Sep 2012 11:37

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